Learning in the combinatorial neural model

IEEE Transactions on Neural Networks

Volumn 9, Issue 5, 1998, Pages 831-847

  Machado, Ricardo J ^a   Barbosa, Valmir C ^b   Neves, Paulo A ^a  

^a PONTIFICAL CATHOLIC UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^b FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

Author keywords

Fuzzy neural networks; Image region analysis; Learning systems; Neural networks; Pattern recognition

Indexed keywords

COMBINATORIAL MATHEMATICS; FUZZY SETS; IMAGE ANALYSIS; MATHEMATICAL MODELS; NEURAL NETWORKS; PATTERN RECOGNITION;

COMBINATORIAL NEURAL MODELS;

LEARNING SYSTEMS;

EID: 0032163067     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.712156     Document Type: Article

References (56)

1. V. C. Barbosa, R. J. Machado, and F. S. Liporace, "A neural system for deforestation monitoring on Landsat images of the Amazon region," Int. J. Approximate Reasoning, vol. 11, pp. 321-359, 1994.
2. J. J. Buckley and E. Eslami, "Fuzzy neural nets: Capabilities," in Fuzzy Modeling: Paradigms and Practice, W. Pedrycz, Ed. Boston, MA: Kluwer, 1996, pp. 167-183.
3. J. J. Buckley and Y. Hayashi, "Fuzzy neural networks: A survey," Fuzzy Sets Syst., vol. 66, pp. 1-13, 1994.
4. _, "Neural nets for fuzzy systems," Fuzzy Sets Syst., vol. 71, pp. 265-276, 1995.
5. G. A. Carpenter and S. Grossberg, "The ART of adaptive pattern recognition by a self-organizing neural network," IEEE Comput., vol. 21, pp. 77-88, 1988.
6. 2)," in Proc. Int. Wkshp. Visual Form, 1991, pp. 165-174.
7. D. Dubois and H. Prade, "A class of fuzzy measures based on triangular norms," Int. J. General Syst., vol. 8, pp. 43-61, 1992.
8. L. Fu, "Knowledge-based connectionism for revising domain theories," IEEE Trans. Syst., Man, Cybern., vol. 23, pp. 173-182, 1993.
9. _, Neural Networks in Computer Intelligence. New York, NY: McGraw-Hill, 1994.
10. S. I. Gallant, "Connectionist expert systems," Commun. ACM, vol. 31, pp. 152-169, 1992.
11. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA: Addison-Wesley, 1989.
12. M. M. Gupta and D. H. Rao, "On the principles of fuzzy neural networks," Fuzzy Sets Syst., vol. 61, pp. 1-18, 1994.
13. R. M. Haralick, K. Shanmugam, and I. Dinstein, "Textural features for image classification," IEEE Trans. Syst., Man, Cybern., vol. SMC-3, pp. 610-621, 1973.
14. J. Hertz, A. Krogh, and R. G. Palmer, Introduction to the Theory of Neural Computation. Redwood City, CA: Addison-Wesley, 1991.
15. G. E. Hinton, "Connectionist learning procedures, "Artificial Intell., vol. 40, pp. 185-234, 1989.
16. K. Hirota and W. Pedrycz, "Knowledge-based networks in classification problems," Fuzzy Sets Syst., vol. 59, pp. 271-279, 1993.
17. V. Honavar and L. Uhr, "A network of neuronlike units that learns to perceive by generation as well as reweighing of links," in Proc. Connectionist Models Summer School, 1988, pp. 472-484.
18. A. Kandel and G. Langholz, Hybrid Architectures for Intelligent Systems. Boca Raton, FL: CRC, 1992.
19. J. M. Keller, M. R. Gray, and J. A. Givens, "A fuzzy k-nearest neighbor algorithm," IEEE Trans. Syst., Man, Cybern., vol. 15, pp. 580-585, 1985.
20. J. M. Keller and D. J. Hunt, "Incorporating fuzzy membership functions into the perceptron algorithm," IEEE Trans. Pattern Anal. Machine Intell., vol. 7, pp. 693-699, 1985.
21. J. M. Keller, R. Krishnapuram, and F. C. Rhee, "Evidence aggregation networks for fuzzy logic inference," IEEE Trans. Neural Networks, vol. 3, pp. 761-769, 1992.
22. J. M. Keller and H. Tahani, "Backpropagation neural networks for fuzzy logic," Inform. Sci., vol. 62, pp. 205-222, 1992.
23. B. Kosko, Neural Networks and Fuzzy Systems. Englewood Cliffs, NJ: Prentice-Hall, 1992.
24. Y. Le Cun, "Generalization and network design strategies," in R. Pfeifer, Z. Schreter, F. Fogelman, and L. Steels, Eds., Connectionism in Perspective. Amsterdam, The Netherlands: North-Holland, 1989, pp. 143-156.
25. Y. Le Cun, J. S. Denker, and S. A. Solla, "Optimal brain damage," in D. S. Touretzky, Ed., Advances in Neural Information Processing Systems, vol. 2. San Mateo, CA: Morgan Kaufmann, 1990, pp. 598-605.
26. B. F. Leão and E. B. Reátegui, "HYCONES: A hybrid connectiomst expert system," in Proc. Annu. Symp. Comput. Applicat. Medical Care, 1993, pp. 461-465.
27. B. F. Leão, E. B. Reátegui, A. Guazzelli, and E. A. Mendonça, "Hybrid systems: A promising solution to better decision support tools," in Proc. World Congr. Medical Inform., Vancouver, Canada, July 1995, pp. 823-827.
28. _, "HYCONES: A hybrid approach to designing decision support systems," MD Comput., vol. 13, pp. 160-161, 1996.
29. S. C. Lee and E. T. Lee, "Fuzzy neural networks," Math. Biosci., vol. 23, pp. 151-177, 1975.
30. C. Lemaréchal, "Nondifferentiable optimization," in Handbooks in Operations Research and Management Sciences, vol. 1, Optimization,G. L. Nemhauser, A. H. G. Rinnooy Kan, and N. J. Todd, Eds. Amsterdam, The Netherlands: North-Holland, 1989, pp. 529-572.
31. F. S. Liporace, R. J. Machado, and V. C. Barbosa, "Equalization of the training set for backpropagation networks applied to classification systems," in Proc. 1st Brazilian Congr. Neural Networks, 1994, pp. 99-103.
32. R. J. Machado and P. A. Neves, "Automatic design of membership functions for pattern classification systems," in Proc. 6th Int. Fuzzy Assoc. World Congr., vol. 2, pp. 33-36, 1995.
33. R. J. Machado and A. F. Rocha, "The combinatorial neural network: A connectionist model for knowledge-based systems," in B. Bouchon, L. Zadeh and R. Yager, Eds., Uncertainty in Knowledge Bases. Berlin, Germany: Springer-Verlag, 1991, pp. 578-587.
34. _, "Evolutive fuzzy neural networks," in Proc. IEEE Int. Conf. Fuzzy Syst., 1992, pp. 493-400.
35. _, "Inference, inquiry, and explanation in expert systems by means of fuzzy neural networks," in Proc. 2nd IEEE Int. Conf. Fuzzy Syst., 1993, pp. 351-356.
36. _, "A method for incremental learning in fuzzy neural networks," in Proc. 1st Brazilian Symp. Neural Networks, 1994, pp. 105-110.
37. _, "Integrating symbolic and neural methods for building intelligent systems," in Proc. Int. Symp. Integrating Knowledge and Neural Heuristics, 1994, pp. 283-292.
38. _, "Inference, inquiry, evidence censorship, and explanation in connectionist expert systems," IEEE Trans. Fuzzy Syst., vol. 5, pp. 443-459, 1997.
39. S. Mitra, "Fuzzy MLP-based expert system for medical diagnosis," Fuzzy Sets Syst., vol. 65, pp. 285-296, 1994.
40. M. C. Mozer and P. Smolensky, "Skeletonization: A technique for trimming the fat from a network via relevance assessment," in Advances in Neural Information Processing Systems, vol. 1, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1989, 107-115.
41. Nath A. K. and T. T. Lee, "On the design of a classifier with linguistic variables as inputs," Fuzzy Sets Syst., vol. 11, pp. 265-286, 1983.
42. D. Nauck and R. Kruse, "Designing neuro-fuzzy systems through backpropagation," in W. Pedrycz, Ed., Fuzzy Modeling: Paradigms and Practice. Boston, MA: Kluwer, 1996, pp. 203-228.
43. S. K. Pal and S. Mitra, "Multilayer perceptron, fuzzy sets, and classification," IEEE Trans. Neural Networks, vol. 3, pp. 683-697, 1992.
44. D. Parisi and M. Sturzenbecker, "Application of fuzzy inferencing techniques to automated classification of defects in semiconductor wafers," in Proc. Fuzzy Logic'94, pp. 350-363.
45. S. H. Peckinpaugh, "An improved method for computing gray-level cooccurrence matrix based on texture measures," Computer Vision, Graphics, and Image Processing, vol. 35, pp. 574-580, 1991.
46. W. Pedrycz, "Fuzzy neural networks and neurocomputations," Fuzzy Sets Syst., vol. 56, pp. 1-28, 1993.
47. W. Pedrycz and A. F. Rocha, "Fuzzy-set-based models of neurons and knowledge-based networks," IEEE Trans. Fuzzy Syst., vol. 1, pp. 254-266, 1993.
48. W. Pree, F. G. Beckenkamp, and S. I. V. da Rosa, "Object-oriented design and implementation of a flexible architecture for decision support systems," in Proc. Int. Conf. on Software Eng. Knowledge Eng., 1997, pp. 382-388.
49. M. Riedmiller and H. Braun, "A direct adaptive method for faster backpropagation learning: The RProp algorithm," in Proc. Int. Conf. Neural Networks, 1993, pp. 586-591.
50. A. F. Rocha, Neural Nets - A Theory for Brains and Machines. Berlin, Germany: Springer-Verlag, 1992.
51. M. Sturzenbecker and D. Parisi, "The recursive fuzzy hypercube," in Proc. Int. Conf. Fuzzy Theory Technol., 1994, pp. 413-417.
52. L. M. Sztandera, "Fuzzy neural trees," Inform. Sci., vol. 90, pp. 157-177, 1996.
53. A. Visa, "A texture classifier-based on neural network principles," in Proc. Int. Joint Conf. Neural Networks, 1990, pp. I-491-496.
54. A. S. Weigend, D. E. Rumelhart, and B. A. Huberman, "Backpropagation, weight elimination, and time series prediction," in Proc. Connectionist Models Summer School, 1990, pp. 65-80.
55. D. Whitley, T. Starkweather, and C. Bogart, "Genetic algorithms and neural networks: Optimizing connections and connectivity," Parallel Comput., vol. 14, pp. 347-361, 1990.
56. H. J. Zimmermann and P. Zysno, "Decisions and evaluations by hierarchical aggregation of information," Fuzzy Sets Syst., vol. 10, pp. 243-260, 1983.